Fujifilm Invests in LPixel, a Venture from the University of Tokyo
Strengthening the Development of AI for Supporting Diagnoses Using Endoscopes

October 29, 2018

FUJIFILM Corporation (President: Kenji Sukeno) recently signed a contract with LPixel Inc., known for its expertise in medical imaging analysis, to invest in the company by subscribing to a third party allocation of new shares. The investment procedures were completed today.

Fujifilm entered into a partnership with LPixel in April this year for the use of AI technology designed to support diagnosing medical images. Following this investment, Fujifilm and Lpixel will first begin work on the development of a system that harnesses LPixel's AI engines for use with Fujifilm's endoscope systems. In the future, the two companies will consider further joint developments to produce AI technology.

LPixel is a venture company launched from the University of Tokyo. It is one of Japan's leading startups in the field of AI-powered medical diagnostic support technology. The company specializes in technology that harnesses high-quality “teacher data*” to achieve efficient learning by AI systems.

Along with the development of in-house AI technology, Fujifilm is actively working to enter partnerships with AI technology vendors in Japan and overseas in possession of high-quality technology in order to improve diagnostics in a wide range of disease fields, developing various services that combine each company's respective AI technology with Fujifilm's own systems. In addition, Fujifilm has also worked to develop AI technology that supports disease diagnosis by analyzing images taken using various medical imaging devices including CT, MRI and DR scans. In April this year, Fujifilm signed a partnership agreement with LPixel. Since then, the two companies have been working on the development of AI-based medical diagnostic support technology that works with Fujifilm's picture archiving and communication system (PACS)**.
LCI is developed to intensify differences in red coloration for enhanced mucosal visualization through the use of advanced image processing technology.
In addition, Fujifilm is currently working to develop AI technology that can enhance endoscopic diagnoses including technology for marking, in real-time, possible locations of lesions during a gastrointestinal endoscopic exam. Through its investment in LPixel, Fujifilm is aiming to further accelerate these developments. Fujifilm's endoscope system incorporates image enhancement technology for improving the rate of discovery of small lesions. This technology includes BLI***, which outputs a high intensity ratio of blue-violet light, developed for high contrast imaging of microvessels , and Linked Color Imaging (LCI) which is designed to intensify differences in red coloration for enhanced mucosal visualization through the use of advanced image processing technology. Fujifilm will develop AI-enhanced diagnostic support system by using the medical images captured using this technology as learning input. Fujifilm is also working to develop AI powered solutions for supporting endoscopic diagnosis including the partial automation of endoscopic examination reporting which works on Nexus, Fujifilm's endoscopic information management system that has the largest market share*4 in Japan.

Fujifilm plans to provide solutions that cater to the needs of various markets and clinical workflows to customers across the globe under the AI technology brand REiLI, which will cover the of AI technology developed for fields including medical image diagnostic support, support for workflows in clinical settings, and also AI technology for medical device maintenance services.

Fujifilm's strategy is to use AI technology to harness the big data generated through the collection of medical and diagnostic information, working to develop and provide various products and services that can meet a diverse range of needs in clinical settings, contributing to even more efficient medical diagnosis and high quality medical treatment, leading to the maintenance and improvement of people's health.

* This is learning data used by an AI system to learn how to respond appropriately to the input of new data.

** Picture Archiving and Communication System uses a server to store images captured using various medical imaging systems including CT, MRI and DR systems.
Clinicians can display these images on terminals within their institution in order to make image-based diagnoses.

*** Blue Light Imaging and Blue Laser Imaging.

*4 On the basis of both units shipped and revenue earned. Data researched by Fujifilm Medical IT Solutions Co., Ltd.